No abstract

Abstract-In recent years many methods providing the ability to recognize rigid obstacles -sedans and trucks -have been developed. These methods provide the driver with relevant information. They are able to cope reliably with scenarios on motorways. Nevertheless, not much attention has been given to image processing approaches to increase the safety of pedestrians in urban environments. In this paper a method for the detection, tracking, and final recognition of pedestrians crossing the moving oberserver's trajectory is suggested. A combination of data-and model-driven approaches is realized. The initial detection process is based on a fusion of texture analysis, model-based grouping of, most likely, the geometric features of pedestrians, and inverseperspective mapping (binocular vision). Additionally, motion patterns of limb movements are analyzed to determine initial object hypotheses. The tracking of the quasi-rigid part of the body is performed by different algorithms that have been successfully employed for the tracking of sedans, trucks, motorbikes, and pedestrians. The final classification is obtained by a temporal analysis of the walking process.

Abstract-In recent years many methods providing the ability to recognize rigid obstacles -sedans and trucks -have been developed. These methods provide the driver with relevant information. They are able to cope reliably with scenarios on motorways. Nevertheless, not much attention has been given to image processing approaches to increase the safety of pedestrians in urban environments. In this paper a method for the detection, tracking, and final recognition of pedestrians crossing the moving oberserver's trajectory is suggested. A combination of data-and model-driven approaches is realized. The initial detection process is based on a fusion of texture analysis, model-based grouping of, most likely, the geometric features of pedestrians, and inverseperspective mapping (binocular vision). Additionally, motion patterns of limb movements are analyzed to determine initial object hypotheses. The tracking of the quasi-rigid part of the body is performed by different algorithms that have been successfully employed for the tracking of sedans, trucks, motorbikes, and pedestrians. The final classification is obtained by a temporal analysis of the walking process.

No abstract

We measured reflectance changes by means of optical imaging of intrinsic signals to study the effects of acute electrical cochlear stimulation on the topography of the cat auditory cortex. After single-pulse electrical stimulation at selected sites of a multichannel implant device, we found topographically restricted response areas representing mainly the high-frequency range in AI. Systematic variation of the stimulation pairs and thus of the cochlear frequency sites revealed a systematic and corresponding shift of the response areas that matched the underlying frequency organization. Intensity functions were usually very steep. Increasingly higher stimulation currents evoked increasingly larger response areas, resulting in decreasing spatial, i.e. cochleotopic, selectivity; however, we observed only slight positional shifts of the focal zones of activity. Electrophysiological recordings of local field potential maps in the same individual animals revealed close correspondence of the locations of the cortical response areas. The results suggest that the method of optical imaging can be used to map response areas evoked by electrical cochlear stimulation, thereby maintaining a profound cochleotopic selectivity. Further experiments in chronically stimulated animals will shed more light on the degree of functional and reorganizational capacities of the primary cortex and could be beneficial for our understanding of the treatment of profound deafness.